Creating Disability Story Videos with Generative AI: Motivation, Expression, and Sharing

要旨

Generative AI (GenAI) is both promising and challenging in supporting people with disabilities (PwDs) in creating stories about disability. GenAI can reduce barriers to media production and inspire the creativity of PwDs, but it may also introduce biases and imperfections that hinder its adoption for personal expression. In this research, we examine how nine PwD from a disability advocacy group used GenAI to create videos sharing their disability experiences. Grounded in digital storytelling theory, we explore the motivations, expression, and sharing of PwD-created GenAI story videos. We conclude with a framework of momentous depiction, which highlights four core affordances of GenAI that either facilitate or require improvements to better support disability storytelling: non-capturable depiction, identity concealment and representation, contextual realism and consistency, and emotional articulation. Based on this framework, we further discuss design implications for GenAI in relation to story completion, media formats, and corrective mechanisms.

著者
Shuo Niu
Clark University, Worcester, Massachusetts, United States
Dylan Clements
Clark University, Worcester, Massachusetts, United States
Hyungsin Kim
Clark University, Worcester, Massachusetts, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Augmenting expression and communication

P1 - Room 120
7 件の発表
2026-04-15 18:00:00
2026-04-15 19:30:00